Method of researching and analyzing information contained in a database

• US 7,117,198 B1
• Filed: 11/28/2000
• Issued: 10/03/2006
• Est. Priority Date: 11/28/2000
• Status: Expired due to Fees

• Current Assignee: ipCapital Group, Inc.
• Original Assignee: ipCapital Group, Inc.
• Inventors: Cronin, John Edward, Bibby, Yu Wang
• Primary Examiner(s): Robinson, Greta
• Assistant Examiner(s): DODDS, HAROLD E
• Application Number:
  US09/723,960
• Time in Patent Office: 2,135 Days
• Field of Search: 707 1- 10, 707100-102, 707/104.1, 707/200, 707/201, 707/203, 704/1, 704/2, 704/7, 704/9, 709/200, 709217-219, 715/500, 715/503, 715/505, 715/513, 715/530, 715/531, 715/700, 715/961, 715/965, 715/966, 715/968, 345/418, 345/440, 345/700, 345/961, 345/965, 345/966, 345/968
• US Class Current: 1/1
• CPC Class Codes: G06F 16/334 Query execution G06F16/335 takes precedence
• CPC Class Codes: G06F 2216/11 Patent retrieval
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching

Abstract

A method (100) of researching and analyzing information contained in documents that belong to a first database (200) and are organized according to a first set of fields (210) for an electronic search and retrieval by a computer (850). The method includes the steps of: a) conducting an electronic search (202) of the first database to retrieve at least one document; b) developing user-defined fields (300); c) reading (310) the at least one document to retrieve information pertaining to the user-defined fields; d) entering into a second database (510) the at least one document, values of the first set of fields for the at least one document, the user-defined fields and the retrieved information pertaining to the user-defined fields; and e) analyzing (506) the information contained in the second database.

Claims

1. A method of researching and analyzing information contained in a plurality of documents belonging to a first database, searchable on a plurality of search fields and having a plurality of search field values, the method comprising the steps of:

a) developing a set of search arguments relating to one or more interests of a user;

b) developing a set of user-defined fields relating to said one or more interests, said set of user-defined fields being distinct from said set of search arguments;

c) searching the first database using at least some of said set of search arguments so as to retrieve a plurality of retrieved documents from among the plurality of documents;

d) reading each of said plurality of retrieved documents so as to extract from each of said plurality of retrieved documents a user-defined field value for at least one user-defined field of said set of user-defined fields so as to obtain a plurality of user-defined field values;

e) entering said plurality of user-defined values extracted in step d) into a second database;

f) entering the ones of the plurality of search field values corresponding to said plurality of retrieved documents into said second database;

g) filling out a high level of abstraction (HLA) framework form so as to form a plurality of HLA clusters; and

h) assigning each of said plurality of retrieved documents to a corresponding respective one of said plurality of HLA clusters.

2. A method according to claim 1, further comprising subsequent to step c) the step of filtering said plurality of retrieved documents based on at least some of said set of search arguments so as to obtain a refined set of documents, step d) being performed relative to said refined set of documents.

3. A method according to claim 1, wherein each of said plurality of HLA clusters has a corresponding cluster identifier and the method further comprises the step of entering into said second database for each of said plurality of retrieved documents one of said cluster identifiers.

4. A method according to claim 1, further comprising the step of associating, for each of said plurality of retrieved documents, a weight with each of at least some of said plurality of user-defined fields.

5. A method according to claim 4, further comprising the step of entering said weights into said second database.

6. A method according to claim 4, further comprising the step of tallying said weights for each of said plurality of retrieved documents.

7. A method according to claim 1, wherein step a) includes the step of at least partially populating a first input form.

8. A method according to claim 7, wherein the step of at least partially populating said first input form comprises populating said first input form with known documents already known to the user.

9. A method according to claim 1, wherein step b) includes the step of at least partially populating a second input form.

10. A method according to claim 9, wherein the step of at least partially populating said second input form includes populating said second input form with answers to questions relating to a business of the user.

11. A method according to claim 10, further comprising the step of assigning weights to at least some of said answers.

12. A method of researching and analyzing information contained in a plurality of documents belonging to a first database, searchable on a plurality of search fields and having a corresponding plurality of search field values, the method comprising the steps of:

a) receiving a set of search arguments relating to one or more interests of a user;

b) receiving a set of user-defined fields relating to said one or more interests, said set of user-defined fields being distinct from said set of search arguments;

c) searching the first database using at least some of said set of search arguments so as to retrieve a plurality of retrieved documents from the plurality of documents;

d) receiving, for each of said plurality of retrieved documents, a user-defined field value for at least one user-defined field of said set of user-defined fields so as to receive a plurality of user-defined field values, said plurality of user-defined field values having been extracted from said plurality of retrieved documents;

e) entering said plurality of user-defined values received in step d) into a second database;

f) entering the plurality of search field values into said second database; and

g) presenting a high level of abstraction (HLA) framework form to a user.

13. A method according to claim 12, further comprising subsequent to step c) the step of filtering said plurality of retrieved documents based on at least some of said set of search arguments so as to obtain a refined set of documents, step d) being performed relative to said refined set of documents.

14. A method according to claim 12, further comprising the step of receiving an HLA cluster identifier for each of said plurality of retrieved documents.

15. A method according to claim 14, further comprising the step of entering each of said cluster identifiers into said second database.

16. A method according to claim 12, further comprising the step of receiving, for each of said plurality of retrieved documents, a weight for each of at least some of said plurality of user-defined fields.

17. A method according to claim 16, further comprising the step of entering said weights into said second database.

18. A method according to claim 16, further comprising the step of tallying said weights for each of said plurality of retrieved documents.

19. A method according to claim 12, wherein step a) includes the step of presenting the user with a first input form for developing said set of search arguments.

20. A method according to claim 12, wherein step b) includes the step of presenting the user with a second input form for developing said set of user-defined fields.

21. A method according to claim 20, further comprising the step of receiving via said second input form answers to a plurality of questions relating to a business of the user.

22. A method according to claim 20, further comprising the step of receiving via said second input form weights for at least some of said answers.

23. A computer readable medium containing computer instructions for researching and analyzing information contained in a plurality of documents belonging to a first database, searchable on a plurality of search fields and having a corresponding plurality of search field values, the computer instructions comprising:

a) a first set of instructions for receiving a set of search arguments relating to one or more interests of a user;

b) a second set of instructions for receiving a set of user-defined fields relating to said one or more interests, said set of user-defined fields being distinct from said set of search arguments;

c) a third set of instructions for searching the first database using at least some of said set of search arguments so as to retrieve a plurality of retrieved documents from the plurality of documents;

d) a fourth set of instructions for receiving, for each of said plurality of retrieved documents, a user-defined field value for at least one user-defined field of said set of user-defined fields so as to receive a plurality of user-defined field values, said plurality of user-defined field values having been extracted from said plurality of retrieved documents;

e) a fifth set of instructions for entering said plurality of user-defined values received in step d) into a second database;

f) a sixth set of instructions for entering the plurality of search field values into said second database; and

g) a seventh set of instructions for presenting a high level of abstraction (HLA) framework form to a user.

24. A computer readable medium according to claim 23, further comprising in addition to the third set of instructions, an eighth set of instructions for filtering said plurality of retrieved documents based on at least some of said set of search arguments so as to obtain a refined set of documents.

25. A computer readable medium according to claim 23, further comprising a ninth set of instructions receiving an HLA cluster identifier for each of said plurality of retrieved documents.

26. A computer readable medium according to claim 23, further comprising a tenth set of instructions for entering each of said HLA cluster identifiers into said second database.

27. A computer readable medium according to claim 23, further comprising an eleventh set of instructions for receiving, for each of said plurality of retrieved documents, a weight for each of at least some of said plurality of user-defined fields.

28. A computer readable medium according to claim 27, further comprising a twelfth set of instructions for entering said weights into said second database.

29. A computer readable medium according to claim 27, further comprising a thirteenth set of instructions for tallying said weights for each of said plurality of retrieved documents.

30. A computer readable medium according to claim 23, wherein said first set of instructions includes instructions for presenting the user with a first input form for developing said set of search arguments.

31. A computer readable medium according to claim 23, wherein said second set of instructions includes instructions for presenting the user with a second input form for developing said set of user-defined fields.

32. A computer readable medium according to claim 31, further comprising a fourteenth set of instructions for receiving via said second input form answers to a plurality of questions relating to a business of the user.

33. A computer readable medium according to claim 32, further comprising a fifteenth set of instructions for receiving via said second input form weights for at least some of said answers.

34. A system for researching and analyzing information contained in a plurality of documents belonging to a first database, searchable on a plurality of search fields and having a corresponding plurality of search field values, the system comprising:

a) a computer;

b) a second database;

c) a first set of instructions executable by said computer for receiving a set of search arguments relating to one or more interests of a user;

d) a second set of instructions executable by said computer for receiving a set of user-defined fields relating to said one or more interests, said set of user-defined fields being distinct from said set of search arguments;

e) a third set of instructions executable by said computer for searching the first database using at least some of said set of search arguments so as to retrieve a plurality of retrieved documents from the plurality of documents;

f) a fourth set of instructions executable by said computer for receiving, for each of said plurality of retrieved documents, a user-defined field value for at least one user-defined field of said set of user-defined fields so as to receive a plurality of user-defined field values, said plurality of user-defined field values having been extracted from said plurality of retrieved documents;

g) a fifth set of instructions executable by said computer for entering said plurality of user-defined values received in step f) into said second database; and

h) a sixth set of instructions executable by said computer for entering the plurality of search field values into said second database; and

i) a seventh set of instructions for presenting a high level of abstraction (HLA) framework form to a user.

35. A system according to claim 34, wherein said second database is contained in said computer.

36. A system according to claim 34, further comprising in addition to the third set of instructions, an eighth set of instructions for filtering said plurality of retrieved documents based on at least some of said set of search arguments so as to obtain a refined set of documents.

37. A system according to claim 34, further comprising a ninth set of instructions receiving an HLA cluster identifier for each of said plurality of retrieved documents.

38. A system according to claim 37, further comprising a tenth set of instructions for entering each of said cluster identifiers into said second database.

39. A system according to claim 34, further comprising an eleventh set of instructions for receiving, for each of said plurality of retrieved documents, a weight for each of at least some of said plurality of user-defined fields.

40. A system according to claim 39, further comprising a twelfth set of instructions for entering said weights into said second database.

41. A system according to claim 39, further comprising a thirteenth set of instructions for tallying said weights for each of said plurality of retrieved documents.

42. A system according to claim 34, wherein said first set of instructions includes instructions for presenting the user with a first input form for developing said set of search arguments.

43. A system according to claim 34, wherein said second set of instructions includes instructions for presenting the user with a second input form for developing said set of user-defined fields.